When a photographed object is in a moving state, it is difficult to accurately capture the photographed object in a traditional photographing manner. For example, when an animal or a baby is being photographed, it is difficult to control the animal or the baby to be in a static state, and therefore, it is difficult to accurately capture the animal or the baby in the traditional photographing manner.
Currently, a photo is automatically generated during video photographing, so that the photographed object is accurately captured. Social network information included in a video is acquired first, then rating and sorting are performed on a video frame according to the social network information included in the video, and finally, one frame or more frames are selected, as a photo required by a user, from various video frames according to scores respectively corresponding to the various video frames.
However, when the photo required by the user is selected using scores separately corresponding to the various video frames determined using the social network information, a video frame is selected according to only the social network information included in the video, thereby leading to relatively low accuracy of video frame selection.